In [2]:
Image(filename="images/pydata_logo.png", width='300px')
Out[2]:
No description has been provided for this image

PyData London News February 2024¶

82nd Meetup, hosted by Man Group¶

@PyDataLondon¶

PyData Code of Conduct¶

https://pydata.org/code-of-conduct/¶

In [3]:
IFrame('https://pydata.org/code-of-conduct/', **default_size)
Out[3]:

NumFOCUS¶

  • US-based charity in support of open-source scientific computing
  • Financial and admin support for many open-source projects
  • Support for many community events
  • https://numfocus.org
In [4]:
IFrame('https://numfocus.org/sponsored-projects', **default_size)
Out[4]:

PyData¶

  • Educational program by NumFOCUS
  • A global community
  • 228 groups across 80 countries world-wide
  • 218,000+ users world-wide (+23,000 per year!)
  • https://www.meetup.com/pro/pydata/
In [6]:
Image('images/pydata-map.png', **default_size)
Out[6]:
No description has been provided for this image
In [7]:
Image('images/pydata-uk-map.png', **default_size)
Out[7]:
No description has been provided for this image

PyData London¶

  • 13,500+ members (Approx +100 members/month, we can do better! Tell a friend! Submit a talk! Need more ⚡)

  • Monthly meetup + annual conference

  • All run by volunteers

  • Propose a Talk: https://london.pydata.org/submit-a-talk/

In [8]:
Image('images/pydata-london-screenshot.png', **default_size)
Out[8]:
No description has been provided for this image

Man Group¶

No description has been provided for this image
  1. The world's largest publicly traded hedge fund company with $161 billion in funds under management as of 2024.
  2. Lots of open positions in both tech and research!
  3. Sponsors PyData London ❤️❤️❤️

Upcoming Conferences¶

Courtesy of https://pythondeadlin.es/¶

In [3]:
IFrame('https://pythondeadlin.es/', **default_size)
Out[3]:

Tonight's Schedule¶

18:30 Doors open¶

19:00 Talks start ⬅️ YOU ARE HERE¶

19:15 Talk #1 + Q&A¶

19:45 Scheduled Lightning talk¶

19:50 Break 🥂¶

20:05 Talk #2 + Q&A¶

20:35 ⚡ Lightning Talk ⚡ + 📣 Community Announcements 📣¶

20:45 to 21:00 We're done 🔜 The Banker 🍻¶

1️⃣ 📊💸 Toolbox of a not-so Data Scientist — Tambe Tabitha Achere¶

This talk is about building data science solutions in scenarios where demos cannot be done on a notebook and dashboards do not suffice as a final deliverable. By the end of this session, the audience will have an idea of how data scientists can build the logic behind full-stack applications without the need to learn a backend framework.

I will do a deep dive into one of my projects and there will be lots of code samples accompanied by explanations that led to design decisions. The project I'll be diving into is one in which the data could not be pulled in so if you've ever had to build for data you couldn't see, this session is for you too. I'll highlight the tools, packages and processes that enabled it to be built.

2️⃣ 🛠️🌐 Boosting Similarity Search With Real-time Stream Processing - Fawaz Ghali¶

The goal of similarity search and vector databases is to find similar results to the search query for unstructured data, such as text, images, and videos. The unstructured data first is vectorized, and stored in a vector format. There are publicly available tools to create vectors from unstructured data; similarly, there are vector databases to store and perform similarity searches.

⚡ Lightning Talks ⚡¶

⚡1️⃣ Open-Source Science (OSSci) - Tim Bonnemann¶

⚡2️⃣ (Maybe) faster Pandas with CuDF on the GPU (perhaps) - Ian Ozsvald¶

🕊️ Tweet #pydatalondon and @pydatalondon 🦆¶

In [ ]: